code: def test_entropy_for_uniform_distribution(self):
      metric = Entropy()
      logits = torch.Tensor([[1, 1, 1, 1], [1, 1, 1, 1]])
      metric(logits)
      numpy.testing.assert_almost_equal(metric.get_metric(), 1.38629436)
      # actual values shouldn't effect uniform distribution:
      logits = torch.Tensor([[2, 2, 2, 2], [2, 2, 2, 2]])
      metric(logits)
      numpy.testing.assert_almost_equal(metric.get_metric(), 1.38629436)
  
      metric.reset()
      assert metric._entropy == 0.0
      assert metric._count == 0.0
  
file_path: magnitude/pymagnitude/third_party/allennlp/tests/training/metrics/entropy_test.py
imports: from __future__ import absolute_import
  import torch
  import numpy
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.training.metrics import Entropy
label_desc: Use image node_id 2 for calling the EntropyTest obj's underlying member method code with example usage: obj.test_entropy_for_uniform_distribution() without return types